LEADER 01127nam--2200361---450- 001 990003074530203316 005 20080418153821.0 010 $a3-540-24061-6 035 $a000307453 035 $aUSA01000307453 035 $a(ALEPH)000307453USA01 035 $a000307453 100 $a20080305d2004----km-y0itay50------ba 101 $aeng 102 $aDE 105 $ay---||||001yy 200 1 $aModular algorithms in symbolic summation and symbolic integration$fJurgen Gerhard 210 $aBerlin [etc.]$cSpringer$dcopyr. 2004 215 $aXII, 224 p.$d24 cm 225 2 $aLecture notes in computer science$v3218 410 0$12001$aLecture notes in computer science$v3218 606 0 $aAlgoritmi 676 $a511.8 700 1$aGERHARD,$bJurgen$0441584 801 0$aITA$bsalbc$gISBD 912 $a990003074530203316 951 $a001 LNCS 3218$b31519/CBS$c001$d00112386 959 $aBK 969 $aSCI 979 $aANGELA$b90$c20080305$lUSA01$h0934 979 $aANGELA$b90$c20080418$lUSA01$h1538 996 $aModular Algorithms in Symbolic Summation and Symbolic Integration$9772838 997 $aUNISA LEADER 00769nam0-22002651i-450 001 990004919470403321 005 20230529112609.0 035 $a000491947 035 $aFED01000491947 035 $a(Aleph)000491947FED01 100 $a19990530g18989999km-y0itay50------ba 101 0 $aita 102 $aIT 105 $ay-------001yy 200 1 $aLingua e letteratura spagnuola dalle origini$fEgidio Gorra 210 $aMilano$cEditore-libraio della Real Casa$d1898 215 $aXVII, 430 p.$d20 cm 700 1$aGorra,$bEgidio$0192920 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990004919470403321 952 $aPB 401$bFil. Mod. 3769$fFLFBC 959 $aFLFBC 996 $aLingua e letteratura spagnuola dalle origini$9523110 997 $aUNINA LEADER 04468nam 2200697Ia 450 001 9911019489903321 005 20200520144314.0 010 $a9786613273000 010 $a9781118141151 010 $a9781283273008 010 $a1283273004 010 $a9781118141144 010 $a1118141148 010 $a9781118141120 010 $a1118141121 024 7 $a10.1002/9781118141151 035 $a(CKB)2550000000054352 035 $a(EBL)693319 035 $a(SSID)ssj0000535867 035 $a(PQKBManifestationID)11341982 035 $a(PQKBTitleCode)TC0000535867 035 $a(PQKBWorkID)10545983 035 $a(PQKB)10849081 035 $a(MiAaPQ)EBC693319 035 $a(CaBNVSL)mat06047599 035 $a(IDAMS)0b00006481692a70 035 $a(IEEE)6047599 035 $a(MiAaPQ)EBC693319 035 $a(OCoLC)757511643 035 $a(PPN)267449178 035 $a(Perlego)1003738 035 $a(EXLCZ)992550000000054352 100 $a20110524d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDigital filters $eprinciples and applications with MATLAB /$fFred J. Taylor 205 $a1st ed. 210 $aHoboken, N.J. $cWiley-IEEE Press$d2012 215 $a1 online resource (310 p.) 225 1 $aIEEE series on digital & mobile communication ;$v30 300 $aDescription based upon print version of record. 320 $aIncludes bibliographical references and index. 327 $aPREFACE ix -- CHAPTER 1 INTRODUCTION TO DIGITAL SIGNAL PROCESSING 1 -- CHAPTER 2 SAMPLING THEOREM 11 -- CHAPTER 3 ALIASING 21 -- CHAPTER 4 DATA CONVERSION AND QUANTIZATION 29 -- CHAPTER 5 THE Z-TRANSFORM 41 -- CHAPTER 6 FINITE IMPULSE RESPONSE FILTERS 53 -- CHAPTER 7 WINDOW DESIGN METHOD 71 -- CHAPTER 8 LMS DESIGN METHOD 83 -- CHAPTER 9 EQUIRIPPLE DESIGN METHOD 95 -- CHAPTER 10 FIR: SPECIAL CASES 113 -- CHAPTER 11 FIR IMPLEMENTATION 127 -- CHAPTER 12 CLASSIC FILTER DESIGN 151 -- CHAPTER 13 IIR DESIGN 167 -- CHAPTER 14 STATE VARIABLE FILTER MODELS 183 -- CHAPTER 15 DIGITAL FILTER ARCHITECTURE 197 -- CHAPTER 16 FIXED-POINT EFFECTS 215 -- CHAPTER 17 IIR ARCHITECTURE ANALYSIS 231 -- CHAPTER 18 INTRODUCTION TO MULTIRATE SYSTEMS 249 -- CHAPTER 19 MULTIRATE FILTERS 263 -- BIBLIOGRAPHY 279 -- APPENDIX 281 -- GLOSSARY 287 -- INDEX 295 330 $aSolution implementations for digital filter design and analysis using MATLABA professional engineer charged with designing digital filters for sophisticated electronic devices needs more than design theory to get the job done. It is also essential to have practical guidance in how to characterize a digital filter, choose among a vast number of filter design options available in MATLAB and other software, make proper design choices, and enhance a computer-generated design into the optimal filter for a target application. In addition, it is important to develop skills that make it possible to take full advantage of MATLAB's implementation support.Digital Filters delivers both the theoretical and practical knowledge needed to design, implement, and analyze digital filters using MATLAB. It covers:. Sampling, data acquisition, data conversion and quantization, and transforms. Finite impulse response (FIR) filter attributes, types, special cases, and implementation. Infinite impulse response (IIR) filter attributes, types, special cases, and implementation. State variables as an IIR architectural description language. Multi-rate digital filter systems properties and case studiesEach topic in Digital Filters is supported with numerous examples, many involving the use of MATLAB. The MATLAB scripts used to generate these examples and graphics are available from an accompanying website. These scripts can be easily copied and pasted into MATLAB's Command Window and re-parameterized to reflect specific digital filter applications and needs. 410 0$aIEEE series on mobile & digital communication ;$v30. 606 $aElectric filters, Digital 606 $aSignal processing$xDigital techniques$xMathematics 615 0$aElectric filters, Digital. 615 0$aSignal processing$xDigital techniques$xMathematics. 676 $a621.3815/324 700 $aTaylor$b Fred J.$f1940-$0771870 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911019489903321 996 $aDigital filters$94419611 997 $aUNINA